class_docstr: Each answer choice sentence is scored independently, where the score is
  the sentence probability normalized by the sentence length.
code: def construct_request_state(
      self,
      prompt: Prompt,
      reference_index: int,
      eval_instance: Instance,
      request_mode: str = "original",
  ) -> RequestState:
      request = Request(
          model=self.adapter_spec.model,
          prompt=prompt.text,
          num_completions=1,
          temperature=0,
          max_tokens=0,
          stop_sequences=[],
          echo_prompt=True,
      )
      return RequestState(
          instance=eval_instance,
          reference_index=reference_index,
          request_mode=request_mode,
          train_trial_index=self.train_trial_index,
          output_mapping=None,
          request=request,
          result=None,
          num_train_instances=prompt.num_train_instances,
          prompt_truncated=prompt.truncated,
      )
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/adaptation/adapters/multiple_choice_separate_adapter.py
imports: from typing import List
  from helm.benchmark.adaptation.prompt import Prompt
  from helm.benchmark.adaptation.request_state import RequestState
  from helm.benchmark.scenarios.scenario import Instance
  from helm.common.request import Request
  from .in_context_learning_adapter import InContextLearningAdapter
label_desc: Use image node_id 2 for calling the MultipleChoiceSeparateAdapter obj's underlying member method code with example usage: obj.construct_request_state(prompt, reference_index, eval_instance, request_mode) and returns: RequestState